A meta-analysis of water vapor deuterium-excess in the midlatitude atmospheric surface layer
Bibliographic record
Abstract
Deuterium-excess (d) in water is a combination of the oxygen (delta O-18) and hydrogen (delta D) isotope ratios, and its variability is thought to indicate the location and environmental conditions of the marine moisture source. In this study, we analyze d of water vapor (d(v)) from six sites, all between 37 and 44 degrees N to examine patterns in the atmospheric surface layer and identify the main drivers of variability. Two sites are in urban settings (New Haven, CT, USA and Beijing, China), two sites are in agricultural settings (Rosemount, MN, USA and Luancheng, China), and two sites are in natural ecosystems, a forest (Borden Forest, Ontario, Canada) and a grassland (Duolun, China). We found a robust diurnal cycle in d(v) at all sites with maximum values during mid-day. Isotopic land surface model simulations suggest that plant transpiration is one mechanism underlying the diurnal pattern. An isotopic large-eddy simulation model shows that entrainment of the free atmosphere into the boundary layer can also produce high d(v) values in mid-day. Daily mid-day means of d(v) were negatively correlated with local mid-day relative humidity and positively correlated with planetary boundary layer height at the North American sites, but not the Chinese sites. The mechanism for these differences is still undetermined. These results demonstrate that within the diurnal time scale, d(v) of the surface air at continental locations can be significantly altered by local processes, and is therefore not a conserved tracer of humidity from the marine moisture source region as has previously been assumed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.011 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".